@langchain/community/dist/embeddings/togetherai.js

Third-party integrations for LangChain.js

import { __exportAll } from "../_virtual/_rolldown/runtime.js";
import { getEnvironmentVariable } from "@langchain/core/utils/env";
import { chunkArray } from "@langchain/core/utils/chunk_array";
import { Embeddings } from "@langchain/core/embeddings";
//#region src/embeddings/togetherai.ts
var togetherai_exports = /* @__PURE__ */ __exportAll({ TogetherAIEmbeddings: () => TogetherAIEmbeddings });
/**
* Class for generating embeddings using the TogetherAI API. Extends the
* Embeddings class and implements TogetherAIEmbeddingsParams.
* @example
* ```typescript
* const embeddings = new TogetherAIEmbeddings({
*   apiKey: process.env.TOGETHER_AI_API_KEY, // Default value
*   model: "togethercomputer/m2-bert-80M-8k-retrieval", // Default value
* });
* const res = await embeddings.embedQuery(
*   "What would be a good company name a company that makes colorful socks?"
* );
* ```
*/
var TogetherAIEmbeddings = class extends Embeddings {
	modelName = "togethercomputer/m2-bert-80M-8k-retrieval";
	model = "togethercomputer/m2-bert-80M-8k-retrieval";
	apiKey;
	batchSize = 512;
	stripNewLines = false;
	timeout;
	embeddingsAPIUrl = "https://api.together.xyz/v1/embeddings";
	constructor(fields) {
		super(fields ?? {});
		const apiKey = fields?.apiKey ?? getEnvironmentVariable("TOGETHER_AI_API_KEY");
		if (!apiKey) throw new Error("TOGETHER_AI_API_KEY not found.");
		this.apiKey = apiKey;
		this.modelName = fields?.model ?? fields?.modelName ?? this.model;
		this.model = this.modelName;
		this.timeout = fields?.timeout;
		this.batchSize = fields?.batchSize ?? this.batchSize;
		this.stripNewLines = fields?.stripNewLines ?? this.stripNewLines;
	}
	constructHeaders() {
		return {
			accept: "application/json",
			"content-type": "application/json",
			Authorization: `Bearer ${this.apiKey}`
		};
	}
	constructBody(input) {
		return {
			model: this?.model,
			input
		};
	}
	/**
	* Method to generate embeddings for an array of documents. Splits the
	* documents into batches and makes requests to the TogetherAI API to generate
	* embeddings.
	* @param texts Array of documents to generate embeddings for.
	* @returns Promise that resolves to a 2D array of embeddings for each document.
	*/
	async embedDocuments(texts) {
		const batches = chunkArray(this.stripNewLines ? texts.map((t) => t.replace(/\n/g, " ")) : texts, this.batchSize);
		let batchResponses = [];
		for await (const batch of batches) {
			const batchRequests = batch.map((item) => this.embeddingWithRetry(item));
			const response = await Promise.all(batchRequests);
			batchResponses = batchResponses.concat(response);
		}
		return batchResponses.map((response) => response.data[0].embedding);
	}
	/**
	* Method to generate an embedding for a single document. Calls the
	* embeddingWithRetry method with the document as the input.
	* @param {string} text Document to generate an embedding for.
	* @returns {Promise<number[]>} Promise that resolves to an embedding for the document.
	*/
	async embedQuery(text) {
		const { data } = await this.embeddingWithRetry(this.stripNewLines ? text.replace(/\n/g, " ") : text);
		return data[0].embedding;
	}
	/**
	* Private method to make a request to the TogetherAI API to generate
	* embeddings. Handles the retry logic and returns the response from the
	* API.
	* @param {string} input The input text to embed.
	* @returns Promise that resolves to the response from the API.
	* @TODO Figure out return type and statically type it.
	*/
	async embeddingWithRetry(input) {
		const body = JSON.stringify(this.constructBody(input));
		const headers = this.constructHeaders();
		return this.caller.call(async () => {
			const fetchResponse = await fetch(this.embeddingsAPIUrl, {
				method: "POST",
				headers,
				body
			});
			if (fetchResponse.status === 200) return fetchResponse.json();
			throw new Error(`Error getting prompt completion from Together AI. ${JSON.stringify(await fetchResponse.json(), null, 2)}`);
		});
	}
};
//#endregion
export { TogetherAIEmbeddings, togetherai_exports };

//# sourceMappingURL=togetherai.js.map